Multicast ad hoc networks Multicast in ad hoc nets Multicast in ad hoc nets Review of Multicasting in wired networks Review of Multicasting in wired networks Tree based wireless multicast Tree based wireless multicast Mesh based wireless multicast – ODMRP Mesh based wireless multicast – ODMRP Performance comparison Performance comparison Scalable multicast Scalable multicast M-LANMAR M-LANMAR Backbone Backbone Reliable, congestion controlled multicast Reliable, congestion controlled multicast RALM, RALM with M-LANMAR RALM, RALM with M-LANMAR

The AINS Scenario FLIR

LANMAR Key insight: nodes move in teams/swarms Key insight: nodes move in teams/swarms Each team is mapped into a logical subnet Each team is mapped into a logical subnet IP-like Node address = IP-like Node address = Address compatible with IPv6 Address compatible with IPv6 Team leader (Landmark) elected in each group Team leader (Landmark) elected in each group Logical Subnet Landmark

LANMAR (cont) LANMAR (cont) Three main components in LANMAR: Three main components in LANMAR: (1) “local ” routing algorithm that keeps accurate routes within local scope < k hops (e.g., Distance Vector) (1) “local ” routing algorithm that keeps accurate routes within local scope < k hops (e.g., Distance Vector) (2) Landmark selection within each logical group (2) Landmark selection within each logical group (3) Landmark routes advertised to all nodes (3) Landmark routes advertised to all nodes Logical Subnet Landmark

LANMAR (cont) LANMAR (cont) A packet to “local” destination is routed directly using local tables A packet to “local” destination is routed directly using local tables A packet to remote destination is routed to corresponding Landmark A packet to remote destination is routed to corresponding Landmark Once the packet is “in sight” of Landmark, the direct route is found in local tables. Once the packet is “in sight” of Landmark, the direct route is found in local tables. Main benefit: routing O/H reduction => scalability Main benefit: routing O/H reduction => scalability Logical Subnet Landmark

LANMAR Review Logical Subnet Landmark LM1 LM2 LM3 source dest Long haul routing local routing 1.Node address = {subnet ID, Host ID} 2.Look up local routing table to locate dest  fail 3.Look up landmark table to find destination subnet  LM1 4.Send a packet toward LM1

Scalable Ad hoc multicasting Multicast (ie, transmit same message to all member of a group) critical in battlefield Multicast (ie, transmit same message to all member of a group) critical in battlefield “Multiple unicast” does not scale “Multiple unicast” does not scale Current ad hoc multicast solutions: inappropriate Current ad hoc multicast solutions: inappropriate They do not exploit affinity team model They do not exploit affinity team model multicast tree approach is “fragile” to mobility; multicast tree approach is “fragile” to mobility; no congestion control; no reliable end to end delivery no congestion control; no reliable end to end delivery Proposed approach: Proposed approach: TEAM Multicast TEAM Multicast

swarm Command post Swarm Leader UAVs: - equipped with video, chemical sensors - read data from ground sensors - “fuse” sensor data inputs - multicast fused data to other teams Team Multicasting

Multicast example Attack! Command Post All Task Force Nodes

Two-tier team multicast: Multicast-Enabled Landmark (M-LANMAR) Extension of LANMAR enabling multicast Extension of LANMAR enabling multicast Inter-team communication: unicast tunneling from the source to the representative of each subscribed team Inter-team communication: unicast tunneling from the source to the representative of each subscribed team Intra-team communication: scoped flooding within a team Intra-team communication: scoped flooding within a team

Source node LM2 LM3 Subscribed Teams LM4 Tunneling to landmarks Flooding Scope = 2 M-LANMAR

Advantages of M-LANMAR Reduced control traffic overhead Reduced control traffic overhead Scalable to thousands of nodes Scalable to thousands of nodes Enhanced Congestion control and Reliability (because of TCP control on unicast tunnels) Enhanced Congestion control and Reliability (because of TCP control on unicast tunnels)

M-LANMAR multicast

M-LANMAR Implementation User level M-LANMAR daemon on Linux User level M-LANMAR daemon on Linux M-LANMAR daemon functions: M-LANMAR daemon functions: LANMAR routing LANMAR routing Group membership management Group membership management Packet forwarding engine for tunneling and scoped flooding Packet forwarding engine for tunneling and scoped flooding Compatible with any conventional multicast application (eg, vic = video conferencing tool from UCB) Compatible with any conventional multicast application (eg, vic = video conferencing tool from UCB)

Testbed configuration 3 teams (= 3 IPv4 subnets), 1 sender, 3 receivers 3 teams (= 3 IPv4 subnets), 1 sender, 3 receivers Dell P4 laptop with Lucent Orinoco b pcmcia card Dell P4 laptop with Lucent Orinoco b pcmcia card CBR traffic (512B/packet, 5~15 packets/sec) CBR traffic (512B/packet, 5~15 packets/sec) Protocols: ODMRP; M-LANMAR Protocols: ODMRP; M-LANMAR Sender

Experimental Results: Delivery Ratio and Control Overhead  M-LANMAR has higher Delivery Ratio than ODMRP: unicast tunneling helps reliable data delivery as it incorporates RTS/CTS/ACK)  M-LANMAR has higher control overhead

Scalability Objective: test M-LANMAR scalability Objective: test M-LANMAR scalability Compared with Compared with ODMRP ODMRP Flooding Flooding Simulation Environment Simulation Environment QualNet QualNet 1000 nodes forming 36 teams 1000 nodes forming 36 teams on 6000 x 6000 m 2 field on 6000 x 6000 m 2 field CBR traffic (512 bytes/packet, 1packet/sec) CBR traffic (512 bytes/packet, 1packet/sec)

Simulation Results As the number of multicast groups increases As the number of multicast groups increases M-LANMAR achieves high delivery ratio (by unicast tunneling and flooding) M-LANMAR achieves high delivery ratio (by unicast tunneling and flooding) ODMRP suffers from large control overhead and collisions ODMRP suffers from large control overhead and collisions

Multiple Unicast v.s. Mesh Structure Builds a mesh between landmarks Load Balancing Better Reliability source landmark

Enhanced Scalability with a Mobile Backbone Multicast across Large systems of swarms does not scale well excessive protocol overhead Long paths break Swarms separate Enter Mobile Backbone! src dst

Simulation study - swarm motion Implemented in QualNet 3.6 Implemented in QualNet 3.6 Total 300 nodes over a 5000 x 5000 field: Total 300 nodes over a 5000 x 5000 field: 20 candidate backbone nodes 20 candidate backbone nodes 14 swarms, 20 ground nodes in each swarm 14 swarms, 20 ground nodes in each swarm Traffic generated from single source to 30 receivers across different groups Traffic generated from single source to 30 receivers across different groups Bandwidth Allocation - Bandwidth Allocation - backbone/ground: 1Mbps backbone/ground: 1Mbps flat network: 2Mbps flat network: 2Mbps Mobile backbone significantly improves delivery in swarm/group motion

Simulation study - random roaming Backbone network improvements for random motion even higher than with swarms Random distribution of 500 nodes on a 5000x5000 field Random distribution of 500 nodes on a 5000x5000 field Nodes move randomly Nodes move randomly Ground network is dense and connected Ground network is dense and connected Single multicast group: one source, 30 receivers Single multicast group: one source, 30 receivers Bandwidth Allocation - Bandwidth Allocation - backbone/ground:1Mbs backbone/ground:1Mbs flat network: 2Mbps flat network: 2Mbps

Conclusions and Future Work M-LANMAR is a scalable multicast protocol designed for large ad-hoc networks with affinity team model M-LANMAR is a scalable multicast protocol designed for large ad-hoc networks with affinity team model Backbone Enhanced multicast: Backbone Enhanced multicast: Backbone + ODMRP achieves better scalability than flat ODMRP (delivery ratio increases up to 50%) Backbone + ODMRP achieves better scalability than flat ODMRP (delivery ratio increases up to 50%) Related work Related work Coexistence of LANMAR and Backbone Coexistence of LANMAR and Backbone Impact of mobility (random, team, etc) Impact of mobility (random, team, etc) Mobility and traffic correlation Mobility and traffic correlation Delay tolerant appls; “data ferrying” Delay tolerant appls; “data ferrying”